How big data is changing the cost of insurance (2024)

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How big data is changing the cost of insurance (1)

By Kim Gittleson

BBC reporter, New York

Dave Pratt winced when his teenage son bought himself a Jeep, thinking of how high the insurance would be on a young driver with a flashy car.

But unlike most parents, Mr Pratt is at the forefront of the insurance industry's efforts to change the way car insurance is priced.

So Mr Pratt, who works for insurer Progressive, installed the company's Snapshot device in his son's car.

It's what's known in the business as a "telematic" device, which monitors the speed his son drives every second and what time of day he drives. The device also beeps three times when his son brakes too suddenly.

When his son accused him of trying to train him to be a better driver, Mr Pratt agreed that was what he was trying to do.

This, he says, is the future of car insurance: being able to monitor individual drivers to give them lower prices but also to make them better drivers.

"Now that we can observe directly how people drive, we think this will change the way insurance works," says Mr Pratt, who adds that Progressive has more than a trillion seconds of driving data from 1.6 million customers.

Sloppy business

Car insurance firms like Progressive in the US, to Tesco Bank in the UK and Generali Group in Italy, are currently in a race to convince consumers that letting them monitor their driving behaviour is actually a good thing.

This is because the technology, while not new, has only become affordable recently.

Also, consumers are just getting used to the idea of being tracking and having their data collected.

Proponents say this shift will reshape the insurance business.

"The way we've done insurance now compared to what we can do is sloppy," says Mike Fitzgerald, senior analyst at Celent, a research firm.

"We're taking tens of thousands of people and saying they all have the same risk profile when in fact they don't.

"Most people are actually overpaying."

This is because traditional insurance looks at averages, as opposed to specifics. You fill out a form saying you're a certain age, and drive a certain type of car, and are a specific gender - and that's basically all the data car companies have to assess your riskiness as driver.

Better big data technologies, like the telematic driving data collected by car companies or even information gathered from social media profiles, can help augment that risk profile.

"If I'm a driver that doesn't drive that frequently, and I have a pattern that would indicate that I drive more carefully than an average person with my profile, then I may be able to save 30-40% on my car insurance, and that's pretty significant," explains Joe Reifel, a partner at A.T. Kearney, a consulting firm.

Social life insurance

It's not just car insurers who want better data on consumers.

Jamie Yoder, head of Pricewaterhouse Cooper's insurance advisory practice, recently wrote a report looking at how sensors - like those used to help monitor workouts - could be used by life insurers looking to evaluate customer health.

And of course, there are the tweets.

"Every insurer we have spoken to has a team that looks at social media. The tools are rudimentary, but the data is being used," says Craig Beattie, also of Celent and an author of a report looking at social media use among insurers.

The challenge is being able to automate those teams, instead of using up precious manpower.

"They're sat on a great deal of opportunity with data but they can't get to it," says Mr Beattie.

Denied benefits for smiling

Of course, there is also the danger of misinterpreting that data.

Nathalie Blanchard offers one cautionary tale.

In 2009, while on leave from her technology job in Bromot, Quebec due to severe depression, she went to the bank one day only to find out her health insurance benefits had been cut off.

The cause? A few Facebook photos in which she was smiling.

The insurance company "determined unilaterally that based upon what they saw on the site, they didn't think that she was disabled and they cut her off," says her lawyer, Thomas Lavin. The case later settled out of court.

Anita Ramasastry, a law professor at the University of Washington, cautions regulations will need to be instituted to make sure that insurers don't overstep into big brother territory.

She asks: "are disclosures being made in a way that consumers understand how their social media information is being used for insurance scoring purposes and is there a way for the consumer to do anything about that?"

Fundamental shift

For now, using big data analytics for insurers is still in the early stages.

Only 2% of the US car insurance market offers an insurance product based on monitoring driving, according to A.T. Kearney's Mr Reifel.

But that proportion is projected to grow to around 10-15% of the market by 2017. And other countries, like Italy and the UK, are already using the data to analyse not just risk profiles but also to determine who is at fault in car accidents.

The future, most analysts agree, is to create a continuous feedback loop between insurers and consumers, so that consumers will react to the big data analyses that insurers do on them and change their behaviour accordingly.

"That's the end game - insurers could not just cover losses if they occur, but actually prevent them," says Mr Beattie.

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How big data is changing the cost of insurance (2024)

FAQs

How has big data changed insurance industry? ›

Big Data Analytics in Insurance

Cloud computing improves the performance of analytics in real-time and in greater depth. It also speeds up machine learning processes. Thanks to this there is also greater personalization of products and services: premiums are tailored in real time to literally any customer.

How can big data reduce costs in healthcare? ›

Knowledge derived from big data analysis gives healthcare providers clinical insights not otherwise available. It allows them to prescribe treatments and make clinical decisions with greater accuracy, eliminating the guesswork often involved in treatment, resulting in lower costs and enhanced patient care.

What are the costs associated with big data? ›

What are the true costs of Big Data? There are multiple studies concluding that an Open Source data warehouse with 30TB of data cost approximately $1,000,000 per year. While Open Source Big Data offers low cost software, the hardware costs are high.

For which function can big data be used by insurance companies? ›

Big data technology allows insurers to work quickly on a customer's profile. They can check their history, decide on a suitable risk class, form a pricing model, automate claims processing, and deliver the best services. A study by McKinsey and Company shows that automation saves 43% of the time of insurance employees.

How can big data change healthcare? ›

Big data will help identify patients who fall through the cracks currently and help clinicians follow up with them, such as those who have not had a doctor's visit in years, those with disease symptoms who never came back for treatment or follow-up, or those who were treated for an acute condition (heart attack) but ...

How technology is changing the insurance industry? ›

Technology invasion in the insurance industry is driving significant changes by improving efficiency, personalizing offerings, and enhancing the overall customer experience. Insurers that embrace these technological advancements are better positioned to stay competitive in a rapidly evolving landscape.

Does big data reduce costs? ›

Integrating big data tools can simplify the process, reducing costs overall. Sophisticated tools have been developed to track the buying journeys of customers.

What is an example of big data in healthcare? ›

Big data examples in health care

Perhaps the most common source of big data in health care is electronic health records (EHRs), which typically contain a patient's medical history, demographic information, medications, immunizations, test results, and progress notes.

How big data is improving healthcare? ›

Big Data can be used, for example, for better diagnosis in the context of comprehensive patient data, disease prevention and telemedicine (in particular when using real-time alerts for immediate care), monitoring patients at home, preventing unnecessary hospital visits, integrating medical imaging for a wider diagnosis ...

What are the hidden costs of big data? ›

These costs include not only the direct expenses of acquiring, storing, processing, and analyzing data, but also the indirect and opportunity costs of managing data quality, security, privacy, ethics, and governance.

What is the big problem with big data? ›

With vast amounts of data generated daily, the greatest challenge is storage (especially when the data is in different formats) within legacy systems. Unstructured data cannot be stored in traditional databases.

What are the three implications of big data? ›

Challenges and implications of Big data:

The important attributes associated with the data sets are; Data is a transmissible and storable computer information; knowledge derives an understanding from the data; and more data, more information, therefore, more knowledge embedded in it.

What are examples of big data in insurance? ›

There are several examples of the important role that big data plays in the insurance sector, such as automobile insurance, life insurance (using the so-called mortality modeling), health insurance, harvest risk, catastrophe risk (such as hurricanes, tornadoes, geomagnetic events, earthquakes, floods, and fires), ...

Why is data so important in insurance? ›

The insurance industry thrives on data, which can drive insights and efficiencies in critical areas such as pricing, risk assessment, claims management, and fraud detection.

How is data analytics transforming the insurance industry? ›

It can also analyze a customer's risk and determine which client is trustworthy or may cause great loss. It can also detect fraud, through which the greatest frauds happen. Customers can use data analytics to know which insurance company gives a minimum price with suitable offers.

How is data used in insurance industry? ›

Data analytics create new capabilities that empower insurers to optimize every function in the insurance value chain with the help of data-driven decision-making. It can also analyze a customer's risk and determine which client is trustworthy or may cause great loss.

What is impacting the insurance industry? ›

Today's insurers are exposed to multiple risks, from financial risks, such as shifting interest rates, changing costs and sources of capital, and increasing claims levels due to consecutive years of significant inflation, to an array of nonfinancial risks, including extreme climate events and generative AI (gen AI).

How does big data impact industries? ›

Why is Big Data Important for Businesses? Big Data provides businesses with valuable insights and helps them make data-driven decisions. It can help businesses improve their operations, products, and services, increase efficiency, and drive revenue growth.

What is the biggest threat to the insurance industry? ›

As the insurance sector grapples with multifaceted challenges, identifying and understanding these risk factors is the first step in crafting a resilient strategy for the future.
  1. Compliance changes. ...
  2. Cybersecurity threats. ...
  3. Technology changes. ...
  4. Climate change & other environmental factors. ...
  5. Talent shortage. ...
  6. Financial risks.
Mar 21, 2024

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